The Bina Bioinformatics team is excited to tell you about our latest research in genetic variation analysis at ISMB 2016 this upcoming weekend in Orlando, Florida. Our Bioinformatics Scientist, Mohammad Sahraeian, will be presenting several significant enhancements made to a previously published, integrative structural variation (SV) caller, MetaSV. Recent enhancements have shown improvements in accuracy and speed at detecting more structural variations types, such as insertions, deletions, inversions and duplications, over the original tool. To learn more about this work, be sure to bookmark and check out the following poster presentation on Sunday afternoon:
Advancements in next-generation sequencing (NGS) technologies have produced massive number of short read sequences, making secondary analysis a challenging big data problem. In this seminar presented at Molecular Tri-Con 2016, Bina’s Senior Director of Bioinformatics, Hugo Lam, shared current approaches at Bina in assessing and improving the accuracy of NGS algorithms. Specifically, he touched on how Bina's research expanded the benchmarking toolset through the availability of a better gold set and a variant simulation and validation framework.
Bina is proud to be sponsoring a free luncheon presentation next week with the Stanford Center for Genomics and Personalized Medicine (SCGPM), where we will present our latest scientific advancements in next-generation sequencing analysis. Register and come hungry!
TIME AND PLACE:
Tuesday, April 19, 2016 from 12:00 PM to 1:00 PM. James H. Clark Center Room S360
The Genome in a Bottle Consortium (GiaB) aims to bring together bioinformaticians from multiple companies and institutes together in order to develop better reference materials to enable clinical practice from whole genome sequencing. Bina is an active member of GiaB and contributes to the validation as well as the enhancement of GiaB reference datasets.
Open-source tools are a natural and necessary fit for academic research. The underlying analysis methods need to be fully transparent to enable reproducibility of published results.
Such transparency may not necessarily be the case in a corporate setting where myriad types of software are employed. While the solutions need to process data in very specific ways and cannot produce erroneous results, the details of methods by which this functionality is implemented needn’t be fully transparent. So, we can see why commercial vendors have long thrived in the corporate domain. But that begs the question, do commercial vendors really have a place in academic research?
With the new year, we’ve launched a new website with the goal of making it even easier for you to find relevant information. In addition to our product, company and careers pages, our top-level menu now highlights our Science section. We’re proud of the contributions that our dedicated Science team has made to advance genome analytics. We believe the tools and methods they have devised – and published – to more accurately detect and interpret variants in next-generation sequencing data are unique and vital.
Blue Collar Bioinformatics (bcbio) is an open source community-developed Python toolkit for performing various secondary analyses while adhering to best practices for each analysis. The bcbio toolkit has gained a lot of traction within the bioinformatics community since it enables researchers to easily run many of the popular analysis workflows using a Python interface. Brad Chapman, who is one of the main contributors to bcbio, has kindly added support for MetaSV  on bcbio to allow MetaSV be run as part of the bcbio analysis. In this process, MetaSV has been enhanced to support four additional popular structural-variant (SV) callers, namely, CNVkit , LUMPY , Manta  and WHAM. Since MetaSV was designed to be extensible, support for additional SV callers was easy to incorporate.
Structural variations (SVs) are said to contribute to genomic diversity as well as genomic disorders. Due to their varying lengths, accurate detection of SVs has been challenging with the relatively short-reads generated from next-generation sequencing (NGS). To improve SV detection accuracy and sensitivity, Bina has devised MetaSV, an algorithm that merges results from multiple detection methods. Its overall sensitivity is further enhanced by incorporating a soft-clip based method to boost insertion detection sensitivity. Watch the following video, where Marghoob Mohiyuddin, our Senior Bioinformatics Scientist and author of MetaSV, presents how the tool improves accuracy of SV calling. Details of the research work is published in Bioinformatics.